Information measures

  • Soofi E
  • Zhao H
  • Nazareth D
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Abstract

This article presents an overview of the concept of information about
random outcomes and measures that quantify information provided by
probability distributions. We also provide a few examples and illustrate
applications of the information measures in a computationally intensive
context, namely cluster analysis. Information measures for the multivariate
normal, Cauchy, and Pareto distributions are presented. Three clustering
algorithms are proposed. The algorithms are used to cluster variables
and observations in a data set .

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Authors

  • E S Soofi

  • H Zhao

  • D L Nazareth

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